Triple
T17403292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BART Fremont line |
E423149
|
entity |
| Predicate | usesRollingStock |
P5426
|
FINISHED |
| Object | BART E car |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: BART E car | Statement: [BART Fremont line, usesRollingStock, BART E car]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BART E car Context triple: [BART Fremont line, usesRollingStock, BART E car]
-
A.
BART A/2 cars
chosen
BART A/2 cars are an early-generation series of electric multiple unit railcars used on the San Francisco Bay Area Rapid Transit system.
-
B.
BART C2 cars
BART C2 cars are a later-generation series of Bay Area Rapid Transit rail vehicles designed to expand and modernize the system’s electric multiple-unit fleet.
-
C.
BART
BART (Bay Area Rapid Transit) is a major rapid transit system serving the San Francisco Bay Area, linking cities like San Francisco, Oakland, and Berkeley with surrounding suburbs and regional transit networks.
-
D.
BART
BART is a sequence-to-sequence transformer model developed by Facebook AI for tasks like text generation, summarization, and translation.
-
E.
DART streetcar
The DART streetcar is a modern urban rail transit service in Dallas, Texas, providing short-distance connections through the downtown and nearby districts as part of the city’s public transportation system.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43b051cc48190872278ee0b52240d |
completed | April 19, 2026, 2:16 a.m. |
Created at: April 10, 2026, 5:45 a.m.